A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data

A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data

One main challenge in tunnel constructions is to predict the tunnel geological conditions without excavation to ensure safety during the construction process. This paper proposes a data-driven framework for real-time interpreting the operating data of tunnel boring machines (TBMs) without interrupti...

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Bibliographic Details
Main Authors: Junhong Zhao, Maolin Shi, Gang Hu, Xueguan Song, Chao Zhang, Dacheng Tao, Wei Wu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Tunnel boring machines
geological-type prediction
operating parameter
neural network
physical-mechanical indexes
Online Access:https://ieeexplore.ieee.org/document/8718274/

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